Medix-AI/coqui-tts
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coqui-tts
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Update librispeech deepspeech recipe

This commit is contained in:
Eren Gölge 2021-10-01 13:34:00 +00:00
parent 3aaf6a28e9
commit 42f77e7185
1 changed files with 20 additions and 16 deletions
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36
recipes/librispeech/stt/deep_speech/train_deep_speech.py
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@ -13,21 +13,27 @@ output_path = os.path.dirname(os.path.abspath(__file__))
if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/train-clean-100"): if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/train-clean-100"):
download_librispeech("/home/ubuntu/librispeech/", "train-clean-100") download_librispeech("/home/ubuntu/librispeech/", "train-clean-100")
if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/train-clean-360"):
download_librispeech("/home/ubuntu/librispeech/", "train-clean-360")
if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/train-other-500"):
download_librispeech("/home/ubuntu/librispeech/", "train-other-500")
if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/dev-clean"): if not os.path.exists("/home/ubuntu/librispeech/LibriSpeech/dev-clean"):
download_librispeech("/home/ubuntu/librispeech/", "dev-clean") download_librispeech("/home/ubuntu/librispeech/", "dev-clean")
# train_dataset_config = BaseDatasetConfig( train_dataset_config1 = BaseDatasetConfig(
# name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/train-clean-100" name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/train-clean-100"
# ) )
# eval_dataset_config = BaseDatasetConfig( train_dataset_config2 = BaseDatasetConfig(
# name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/dev-clean" name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/train-clean-360"
# ) )
train_dataset_config = BaseDatasetConfig( train_dataset_config3 = BaseDatasetConfig(
name="ljspeech", name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/train-other-500"
meta_file_train="metadata.csv", )
path="/home/ubuntu/ljspeech/LJSpeech-1.1/",
eval_dataset_config = BaseDatasetConfig(
name="librispeech", meta_file_train=None, path="/home/ubuntu/librispeech/LibriSpeech/dev-clean"
) )
@ -59,16 +65,16 @@ config = DeepSpeechConfig(
mixed_precision=True, mixed_precision=True,
max_seq_len=500000, max_seq_len=500000,
output_path=output_path, output_path=output_path,
train_datasets=[train_dataset_config], train_datasets=[train_dataset_config1, train_dataset_config2, train_dataset_config3],
# eval_datasets=[eval_dataset_config], eval_datasets=[eval_dataset_config]
) )
# init audio processor # init audio processor
ap = AudioProcessor(**config.audio.to_dict()) ap = AudioProcessor(**config.audio.to_dict())
# load training samples # load training samples
train_samples, eval_samples = load_stt_samples(train_dataset_config, eval_split=True) train_samples, _ = load_stt_samples(config.train_datasets, eval_split=False)
# eval_samples, _ = load_stt_samples(eval_dataset_config, eval_split=False) eval_samples, _ = load_stt_samples(config.eval_datasets, eval_split=False)
transcripts = [s["text"] for s in train_samples] transcripts = [s["text"] for s in train_samples]
# init tokenizer # init tokenizer
@ -81,13 +87,11 @@ config.vocabulary = tokenizer.vocab_dict
model = DeepSpeech(config) model = DeepSpeech(config)
# init training and kick it 🚀 # init training and kick it 🚀
# args, config, output_path, _, c_logger, tb_logger = init_training(TrainingArgs(), config)
trainer = Trainer( trainer = Trainer(
TrainingArgs(), TrainingArgs(),
config, config,
output_path, output_path,
model=model, model=model,
tokenizer=tokenizer,
train_samples=train_samples, train_samples=train_samples,
eval_samples=eval_samples, eval_samples=eval_samples,
cudnn_benchmark=False, cudnn_benchmark=False,